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Two-Dimensional Retention Indices Improve Component Identification in Comprehensive Two Dimensional Gas Chromatography of Saffron Ming Jiang, Chadin Kulsing, Yada Nolvachai, and Philip John Marriott Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.5b00953 • Publication Date (Web): 03 May 2015 Downloaded from http://pubs.acs.org on May 14, 2015

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Analytical Chemistry

254x190mm (96 x 96 DPI)

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Analytical Chemistry Jiang et al.

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GC×GC Retention Indices

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Two-Dimensional Retention Indices Improve

3

Component Identification in Comprehensive Two

4

Dimensional Gas Chromatography of Saffron

5

Ming Jianga, Chadin Kulsingb, Yada Nolvachaib and Philip J. Marriottb*

6 a

7

School of Pharmacy, Tongji Medical College, Huazhong University of Science & Technology, #13 Hangkong Road, Wuhan, Hubei 430030, PR China

8 9

b

Australian Centre for Research on Separation Science, School of Chemistry, Monash University, Wellington Road, Clayton, VIC 3800, Australia

10 11 12

Submitted to

13

Analytical Chemistry - ac-2015-00953aR1

14 15 16 17

Corresponding Author *E-mail: [email protected] Tel: + 61 3 99059630; Fax: + 61 3 99058501

18 19

Abbreviations

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GC: gas chromatography; GC×GC: comprehensive two-dimensional gas chromatography;

21

MS: mass spectrometry; QTOFMS: quadrupole time-of-flight mass spectrometry;

22

accTOFMS: accurate mass mass spectrometry; I: retention index; SPME: solid phase micro

23

extraction

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ABSTRACT

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Comprehensive two-dimensional gas chromatography hyphenated with accurate mass time-

28

of-flight mass spectrometry (GC×GC−accTOFMS) was applied for improved analytical

29

accuracy of saffron analysis, by using retention indices in the two-dimensional separation.

30

This constitutes 3 dimensions of identification. In addition to accTOFMS specificity, and first

31

dimension retention indices (1I), a simple method involving direct multiple injections with

32

stepwise isothermal temperature programming is described for construction of isovolatility

33

curves for reference alkane series in GC×GC. This gives access to calculated second

34

dimension retention indices (2I). Reliability of the calculated 2I was evaluated by using a

35

Grob test mixture, and saturated alkanes, revealing good correlation between previously

36

reported I values from the literature, with R2 correlation being 0.9997. This essentially

37

recognises the retention property of peaks in the GC×GC 2D space as being reducible to a

38

retention index in each dimension, which should be a valuable tool supporting identification.

39

The benefit of

40

demonstrated by the progressive reduction of the number of possible compound matches for

41

peaks observed in saffron. 114 analytes were assessed according to 1I and 2I values within

42

±20 index unit of reference values, and by MS spectrum matching above a match statistic of

43

750 (including mass accuracy of the molecular ion 750 was used), and other reference literature.

223



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3.

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Results and discussion

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Effects of choice of different column sets, T programs, and carrier flow rate on separation of

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saffron volatiles, and sorption T for SPME, were investigated by using GC−FID and

228

GC×GC−FID. A suitable experimental condition shown in the Experimental section was

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selected based on these investigations. Compared to the result provided on a non-polar –

230

polar column set, shown in Supporting Information Figure S1A, the column set comprising

231

of 1D SUPELCOWAX 10 and 2D Rxi-5Sil MS columns provided clearer separation of both

232

the many trace components as well as high concentration analytes in saffron, and minimises

233

wraparound (Figure S1B). This column set was thus applied for further analysis with

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GC×GC−accTOFMS (Figure 2A). Although the same GC×GC conditions were applied, the

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change of detector from FID to TOFMS slightly affected separation results, due to

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differences in outlet pressures (being about 14.7 and 0 psi in FID and TOFMS, respectively),

237

and

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GC×GC−accTOFMS result in Figure 2A revealed good separation of >600 compounds

239

(estimated from the numbers of peak contours in the contour plot) in saffron within a single

240

analysis.

understandably

detector

responses

were

significantly

different.

Overall

the

241 242

Mass fragmentation analysis

243

Conventionally, identification of volatile compounds in Traditional Chinese Medicine (TCM)

244

by using 1D GC is based on comparison of the compound mass spectra with those in libraries.

245

When employing the NIST library, 213 peaks were identified in the saffron sample with

246

match and reverse match score values being ≥750. It should be noted that a high threshold

247

score of spectrum similarity may introduce a high rate of false negative identification. There

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is a potential for low abundance or co-eluting compounds to have a low match. Thus, there

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can be a risk of rejection of these compounds that might have acceptable properties (i.e. to

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pass both 1I and 2I filters), but lower MS match. However, since GC×GC is a high resolution

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technique where each peak can be well resolved and concentrated due to the cryogenic

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focusing effect which increases the signal to noise ratios, we could expect to mostly observe

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high match scores in our case. The threshold of 750 is considered not too high in this work

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resulting in >400 compounds to be identified for each peak by MS. As expected, many of

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them had more than one matching library entry with very similar score. By taking the peak

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with 1tR = 32.5 min and 2tR = 2.08 s (see compound 100 in Table 2) for example, the NIST


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library search for this analyte revealed 5 compounds with relatively high match factor (names

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according to the NIST library): 2-butanone,4-(2,6,6-trimethyl-1-cyclohexen-1-yl)-, 2-

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butanone,4-(2,2-dimethyl-6-methylenecyclohexyl)-,

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cyclohexen-1-yl)-, γ-elemene and cyclohexane,1-ethenyl-1-methyl-2-(1-methylethenyl)-4-(1-

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methylethylidene)- according to descending order of match scores (averaged between match

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and reverse match). By default, the compound with the highest match score might be chosen

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as the appropriately identified compound, even though other compounds also have very

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closely matching scores. But this ignores much supporting, corroborating or confounding

265

information, such as retention indices on the GC column, and taking into consideration the

266

lack of specificity of MS analysis especially for isomers. Indeed, further interpretation with

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literature I data revealed 2-butanone,4-(2,6,6-trimethyl-1-cyclohexen-1-yl)- (having the

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highest MS score) does not agree with the 1I and 2I

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indicating ambiguity in compound identification based solely on a library search. This is a

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universal concern for almost all analysis tasks using separations with MS.

3-buten-2-ol,4-(2,6,6-trimethyl-1-

values on the respective phases,

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The use of TOFMS provides exact mass analysis for further confirmation of each compound.

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However, there are significant numbers of isomeric species (e.g. various chemical subclasses

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of terpenes) in saffron which could not be differentiated solely by exact mass due to isobaric

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molecular ions and/or similar fragmentation patterns. For the identification of the peak above,

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though the exact mass analysis showed that γ-elemene and cyclohexane,1-ethenyl-1-methyl-

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2-(1-methylethenyl)-4-(1-methylethylidene)- have mass differences larger than 50 ppm, it

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was still not possible to identify the peak as the other three compounds also have the same

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chemical formula. Furthermore, not all molecular ions will necessarily be observed with hard

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(electron) ionisation applied in the study of TCM, indicating that other auxiliary methods

281

were required for further identification.

282 283

Retention index analysis

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The most reliable method to ascertain peak identification is to employ authentic standard co-

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injection - often economically prohibitive, and sometimes simply impossible for ‘unknowns’.

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Retention index (I) values obtained from GC analysis are very useful to provide

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supplementary data to reduce errors in compound identification in many samples, and

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probably more so in matrices such as essential oils, petrochemicals, forensic toxicology and

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other areas. By comparison of 1I values herein with those reported in literature, a large

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number of possible compounds provided by the NIST library search could be reduced. For



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example, the calculated 1I values of the peak above (compound 100 in Table 2) was 1949.

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NIST library proposed three further likely possible compounds for the identity of this target

293

peak: 2-butanone, 4-(2,6,6-trimethyl-1-cyclohexen-1-yl)-, 2-butanone, 4-(2,2-dimethyl-6-

294

methylenecyclohexyl)- and 3-buten-2-ol, 4-(2,6,6-trimethyl-1-cyclohexen-1-yl)-. Their I

295

values were reported to be 1854, 1798 and 1939, respectively. Within a tolerance of ±20 of

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the I value, only the third compound met this criterion for match with the compound, thus

297

suggesting this as the most probable identity of this target peak. According to the literature

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documenting the accuracy associated with the use of I values,26 an estimation of accuracy

299

threshold can be given. Under a single slow ramping temperature program applied here and

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conventional GC×GC analysis, the average error of elution time predicted in one lab by using the I

301

values calculated from the other lab (but still using the same column) can be about ±4 s corresponding

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to up to 1.4% of time of the first eluting compound in that study (ethylbenzene). In our study, 2I

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generally showed higher error values than those of 1I. We thus considered 2I as the limiting case for

304

the selection of the accuracy threshold. The highest error in the calculation for 2I can be found in this

305

study for analytes with 1tR > 30 min and 900 < 2I < 1000 (which is benzyl alcohol, see compound 97

306

in Table S1) where isovolatility curves are very close (however, it is still possible to calculate I

307

values). With a 1.4% error, the 2I error value can be about ±26 I unit (note that the observed value

308

here is -12). Together with the aim to present no more than 114 analytes, the selection of ±20 here

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was thus reasonable. Though the use of 1I values and the TOFMS spectrum match were found

310

to be useful to improve identification, analysis of analytes in GC×GC analysis suggests a

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further possibility to add greater informing power for identification – the 2I information. It is

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noted that I values of many compounds separated with the 1D polar column cannot be found

313

from literature (which have a greater number of I values on non-polar columns). Furthermore,

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for some structural isomers present in complex samples such as essential oil in TCMs, 1D GC

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provides incomplete separation, resulting in assignment of very similar or the same I values

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for these isomers. Given the imprecision of I data comparison with literature, the problem is

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compounded. Even with 1I of the compounds provided by the NIST library, reliable

318

identification is still not achievable in many cases. As a further example, for the peak with 1tR

319

= 21.27 min and 2tR = 2.53 s (see 55 in Table 2) the NIST search resulted in 6 isomers with

320

match scores being ≥750. 1I comparison showed that 4 analytes had 1I values at variance with

321

literature values within ±20, and therefore were screened out (note that this is predicated on

322

the correctness of the literature data and use of equivalent column types for I value

323

comparison). Thus two analytes had similar 1I values, and so assignment was still ambiguous.

324

An additional tool for refinement of compound identification is still required.


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Construction of isovolatility curves and measurement of 2I data

327

In this study, multiple direct injections of a mixture of alkanes in hexane solvent with several

328

stepwise isothermal oven T programs were performed (Experimental section). Cryogenic

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modulation with a long modulation period (4.00 min) was employed to ensure that all the

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alkanes in each injection were trapped and accurately released simultaneously from the end

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of the 1D column, and that alkanes of interest completely eluted to the detector within a

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suitable period when the oven T was kept at each constant T setting. It is not compulsory that

333

every alkane should be eluted at every isothermal step. For example after injection at low

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oven temperature, C24 just stayed inside the 1D column until the oven temperature was high

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enough to elute this alkane and the corresponding 2tR was calculated at the T this compound

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eluted. In the preliminary experiment, the alkane mixture (C8–C22 and C24) was analysed in

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1D GC using the same oven temperature condition employed in the GC×GC experiment, and

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thus the information of the 1tR of the every alkane in 1D GC was obtained. Combining this 1tR

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information and the precisely controlled release time of the modulator in the GC×GC

340

analysis, we could predict which and how many alkanes could enter the second column in

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each modulator cycle. The corresponding GC×GC result is shown in Figure 3A revealing

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that most of the alkanes were completely eluted before the end of each modulation event. The

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broad bands of solvent peaks in the 2D plot were clearly separated from the reference alkane

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standards – the hexane solvent is not trapped by the cryogenic modulator, always eluting

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about 4 min after each injection with the investigated experimental condition. Note that the

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modulation period should be long enough to ensure the complete elution of all alkanes

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without any remaining in the column before the next isothermal elution step. This avoids

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wraparound which sometimes occurs in conventional GC×GC with the modulation period set

349

at too short a setting.

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Solvent peak times may be ignored. The reference alkane peak positions were reconstructed

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to obtain a clean 2D space (Figure 3B), using Microsoft Excel. 1tR vs 2tR curves of all alkanes

353

were well fitted to polynomial functions up to power six (with R2 > 0.9995). To use the

354

information of alkanes presented in Figure 3B, it is necessary to assess the accuracy of 2I

355

values calculated from the polynomial functions. The offset of 2I value calculated from the

356

polynomial functions can then be used to infer the 2I variation window. Herein, retention time

357

was observed with 2 digits in the time unit (s) which is sufficient for the accuracy of the 2I



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358

value within 1 index unit. As seen in Figure 3B, relatively large coverage of the reference

359

peak retention times in the 2D space was obtained allowing approximation of 2tR of alkanes at

360

any respective 1tR of analytes of interest. This result was obtained from three sets of multiple

361

injection experiments, and included a suitable range of alkanes.

362 363

To test the accuracy of the 2I plot established here, the alkane mixture and the Grob Test Mix

364

were analysed with the same oven T program as used for saffron sample analysis (see dashed

365

line in Figure 1). Note that wraparound occurs in the 2D plot using a PM of 6 s (Figure 2A)

366

for some analytes; this should be taken into account for calculation of analyte 2tR values. The

367

use of a long PM (18 s) resulted in a 2D plot without wraparound (Figure 2B). However use

368

of excessive PM significantly reduces 1D resolution – compare the reconstructed 1D GC trace

369

along the upper axis of Figure 2A with that in 2B, where 18 s results in further loss of

370

resolution. Therefore, for reliable calculation of 2tR, PM of 6 s and 18 s were both employed

371

for the two mixtures above and the saffron sample, respectively. The calculated 2I values of

372

the two mixtures are listed in Table 1. These values are in agreement with the I values

373

reported from literature with differences being within ±20 index units. This demonstrates that

374

the isovolatility curves in Figure 3B could be used for reliable calculation of 2I values in

375

GC×GC. Note that the I value of 2-ethylhexanoic acid here was significantly different to the

376

literature value, since this peak is located at low 2tR where the alkane isovolatility curves are

377

poorly separated as illustrated in Figure 3B, which arises for 1tR > 30 min and 2tR < 2 s. This

378

applies to elution of very polar solutes on the non-polar 2D column, which has a

379

correspondingly very short 2tR value and leads to a large error in 2I.

380 381

Completing the calculated values of 2I , all the information obtained from a single analysis of

382

saffron with GC×GC−TOFMS were combined, resulting in greater confidence in tentative

383

identification of compounds in Table S1. Referring again to the peak at 1tR = 21.27 min, and

384

2

385

arose, by adding 2I data, this peak could be now more securely identified as 1,4-diethyl-2-

386

methylbenzene. The generalised process of application of MS library searching, with 1I and 2I

387

to provide more certain identification of this target peak is illustrated in Figure 4, and the

388

role of 2I as part of the strategy to support compound confirmation in reducing the number of

389

possible compounds from six to one is demonstrated.

tR = 2.53 s (55 in Table 2) where two compounds with very similar 1I and MS match scores

390


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Tentative identification of compounds in the saffron sample

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By considering both 1I and 2I values, 114 out of 213 analytes in the saffron sample were now

393

reliably confirmed as shown in Table S1, some of which are extracted into Table 2 for

394

illustration, emphasising the importance of 1I and 2I to reduce false identification. Examples

395

and the related data involving application of the filters based on mass fingerprint library,

396

exact mass, 1I and 2I values are provided in Table S3 illustrating determination of possible

397

compounds based on their total MS library matches and progressive application of the 1I and

398

2

399

observed in this study. One possible reason is that saffron samples were obtained from

400

different locations or with different treatment processes, which may generate secondary

401

metabolites. The other reason is that although some previously reported compounds were also

402

confirmed in our saffron sample according to the NIST library with high match scores, their I

403

values did not match well with literature values, suggesting possible misidentification in

404

earlier studies. For example, although 2,6,6-trimethylcyclohex-2-en-1-one, 2,6,6-trimethyl-3-

405

oxocyclohex-1-ene-1-carbaldehyde, 2(4H)-benzofuranone, 5,6,7,7a-tetrahydro-3,6-dimethyl-

406

and 2-hydroxy-3,5,5-trimethylcyclohex-2-ene-1,4-dione had match quality ≥750 by using the

407

NIST library, their I values were significantly different from literature values 6,7,28,29. Since the

408

criteria used in this study is that compound identification is acceptable only when both 1I and

409

2

410

listed in Table S1 and Table 2.

I filters to refine the data. Several compounds reported in previous literature 6,7,27-29 were not

I values differ from literature within ±20, these analytes were not added to the compounds

411 412

Although many analytes were necessarily excluded as above, the number of the analytes

413

identified in Table S1 was still much greater than the maximum number expected from the

414

identification of volatile compounds in saffron samples by using 1D GC. This should be due

415

to the higher peak capacity and sensitivity of GC×GC compared to 1D GC, with the former

416

system especially useful for trace analysis.30

417 418

4.

Conclusion

419 420

This study demonstrates the power of GC×GC−TOFMS to provide improved tentative

421

identification of 114 compounds in saffron, within a single analysis. The new and simple

422

approach for the construction of isovolatility curves of alkanes for the determination of 2I

423

values was also established, to allow improved reliability of compound confirmation,



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424

according to the integrated information from MS library searching, accurate mass analysis, 1I

425

and 2I values. Once the 2D data for the alkane reference compounds are calculated, this same

426

dataset can be used for any other sample acquired under the same conditions, and so it should

427

be a relatively straightforward task to either acquire 2I values for other samples, but also to

428

populate a database with results for standards in order to acquire data for columns that require

429

reference data. Beside improved analyte peak capacity, the potential of GC×GC to remove

430

some ambiguity in library searching for complex sample analysis is clearly demonstrated.

431

Accurate mass analysis provided by TOFMS further strengthens the analysis, with mass

432

accuracy below 20 ppm for all the studied analytes, to increase the number of compounds

433

reported for saffron. This study will provide added surety of compound confirmation

434

especially for complex samples for which GC×GC is well suited.

435 436

Acknowledgements

437

MJ is grateful for the support of this work by the National Natural Science Foundation of

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China (No. 51173057). PJM acknowledges the Australian Research Council for a Discovery

439

Outstanding Researcher Award; DP130100217. The authors acknowledge Agilent

440

Technologies for provision of support for some of the facilities used in this study.

441


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(1) Alavizadeh, S. H.; Hosseinzadeh, H. Food Chem. Toxicol. 2014, 64, 65-80. (2) Bolhassani, A.; Khavari, A.; Bathaie, S. Z. Biochim. Biophys. Acta 2014, 1845, 20-30. (3) Hausenblas, H. A.; Saha, D.; Dubyak, P. J.; Anton, S. D. J. Integr. Med. 2013, 11, 377383. (4) Anastasaki, E.; Kanakis, C.; Pappas, C.; Maggi, L.; del Campo, C. P.; Carmona, M.; Alonso, G. L.; Polissiou, M. G. Eur. Food Res. Technol. 2009, 229, 899-905. (5) Tarantilis, P. A.; Beljebbar, A.; Manfait, M.; Polissiou, M. Spectrochim. Acta, Part A 1998, 54, 651-657. (6) Jalali-Heravi, M.; Parastar, H.; Ebrahimi-Najafabadi, H. J. Chromatogr. A 2009, 1216, 6088-6097. (7) D'Auria, M.; Mauriello, G.; Rana, G. L. Flavour Fragrance J. 2004, 19, 17-23. (8) Marriott, P. J.; Chin, S.-T.; Maikhunthod, B.; Schmarr, H.-G.; Bieri, S. TrAC, Trends Anal. Chem. 2012, 34, 1-21. (9) Chin, S.-T.; Marriott, P. J. Chem. Commun. 2014, 50, 8819-8833. (10) Ochiai, N.; Ieda, T.; Sasamoto, K.; Takazawa, Y.; Hashimoto, S.; Fushimi, A.; Tanabe, K. J. Chromatogr. A 2011, 1218, 6851-6860. (11) Chin, S.-T.; Novachai, Y.; Marriott, P. J. Chirality 2014, 26, 747-753. (12) Mezcua, M.; Malato, O.; Garcia-Reyes, J. F.; Molina-Diaz, A.; Fernandez-Alba, A. R. Anal. Chem. 2009, 81, 913-929. (13) Nolvachai, Y.; Kulsing, C.; Marriott, P. J. Crit. Rev. Environ. Sci. Technol. 2015 DOI: 10.1080/10643389.2015.1010431. (14) Mitrevski, B.; Marriott, P. J. J. Chromatogr. A 2014, 1362, 262-269. (15) Kulsing, C.; Nolvachai, Y.; Zeng, A. X.; Chin, S.-T.; Mitrevski, B.; Marriott, P. J. ChemPlusChem 2014, 79, 790-797. (16) Beens, J.; Tijssen, R.; Blomberg, J. J. Chromatogr. A 1998, 822, 233-251. (17) Nolvachai, Y.; Kulsing, C.; Marriott, P. J. Anal. Chem. 2015, 87, 538-544. (18) Bieri, S.; Marriott, P. J. Anal. Chem. 2008, 80, 760-768. (19) Bieri, S.; Marriott, P. J. Anal. Chem. 2006, 78, 8089-8097. (20) Yang, M. Y. Simultaneous dual column retention indices of FAME in GCxGC. RMIT University2007. (21) von Meuhlen, C.; Marriott, P. J. Anal. Bioanal. Chem. 2011, 401, 2351-2360. (22) Tudor, E. J. Chromatogr. A 1999, 858, 65-78. (23) Gonzalez, F. R.; Nardillo, A. M. J. Chromatogr. A 1999, 842, 29-49. (24) Zeng, A. X.; Chin, S. T.; Nolvachai, Y.; Kulsing, C.; Sidisky, L. M.; Marriott, P. J. Anal. Chim. Acta 2013, 803, 166-173. (25) Lebrón-Aguilar, R.; Quintanilla-López, J. E.; García-Domínguez, J. A. J. Chromatogr. A 2002, 945, 185-194. (26) Barnes, B. B.; Wilson, M. B.; Carr, P. W.; Vitha, M. F.; Broeckling, C. D.; Heuberger, A. L.; Prenni, J.; Janis, G. C.; Corcoran, H.; Snow, N. H.; Chopra, S.; Dhandapani, R.; Tawfall, A.; Sumner, L. W.; Boswell, P. G. Anal. Chem. 2013, 85, 11650-11657. (27) Anastasaki, E.; Kanakis, C.; Pappas, C.; Maggi, L.; del Campo, C. P.; Carmona, M.; Alonso, G. L.; Polissiou, M. G. Eur. Food Res. Technol. 2009, 229, 899-905. (28) Jalali-Heravi, M.; Parastar, H.; Ebrahimi-Najafabadi, H. Anal. Chim. Acta 2010, 662, 143-154. (29) Carmona, M.; Zalacain, A.; Salinas, M. R.; Alonso, G. L. Crit. Rev. Food Sci. 2007, 47, 145-159. (30) Klee, M.; Cochran, J.; Merrick, M.; Blumberg, L. M. J. Chromatogr. A 2015, 1383, 151159.



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(31) Nogueira, P. C. L.; Bittrich, V.; Shepherd, G. J.; Lopes, A. V.; Marsaioli, A. J. Phytochemistry 2001, 56, 443-452. (32) Varlet, V.; Knockaert, C.; Prost, C.; Serot, T. J. Agric. Food Chem. 2006, 54, 3391-3401. (33) Rostad, C. E.; Pereira, W. E. J. High Resolut. Chromatogr. 1986, 6, 328-334. (34) Alissandrakis, E.; Tarantilis, P. A.; Harizanis, P. C.; Polissiou, M. J. Agric. Food Chem. 2007, 55, 8152-8157. (35) Pino, J. A.; Mesa, J.; Munoz, Y.; Marti, M. P.; Marbot, R. J. Agric. Food Chem. 2005, 53, 2213-2223. (36) Dharmawan, J.; Kasapis, S.; Curran, P.; Johnson, J. R. Flavour Fragrance J. 2007, 22, 228-232. (37) Nickavar, B.; Salehi-Sormagi, M. H.; Amin, G.; Daneshtalab, M. Pharm. Biol. 2002, 40, 448-449.

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Page 19 of 26


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

506


Page 18

Figure and Table captions

507 508

Figure 1. Oven temperature program settings for the construction of isovolatility curves

509

(using a stepwise isothermal T program, solid line, for alkanes) and for GC×GC separation of

510

saffron (dashed line).

511 512

Figure 2. 2D contour plots of saffron sample analysed by GC×GC–TOFMS with modulator

513

period of (A): 6 s and (B): 18 s.

514 515

Figure 3. (A): 2D contour plot obtained with multiple injections of n-alkanes (C8-C22, C24)

516

in hexane analysed by GC×GC−TOFMS and (B): Two-dimensional retention map

517

(isovolatility curves) for the alkanes generated from three multiple injection experiments with

518

different stepwise isothermal T programs, an example of which is given in Figure 1 (solid

519

line).

520 521

Figure 4. Data analysis in GC×GC−TOFMS, illustrating an example that initially proposed 6

522

compounds that gave MS match factors ≥ 750, then application of 1I and 2I to progressively

523

reduce the number of possible compounds that match retention indices within I ± 20, for

524

identification of a peak at 1tR = 21.27 min and 2tR = 2.53 s.

525 526

Table 1. Comparison of 2I values for some compounds obtained in this study, and literature

527

values. Correlation between calculated and literature values gives an R2 of 0.9997.

528 529

Table 2. Tentatively identified compounds in the saffron sample analysed by GC×GC–

530

TOFMS based on MS library, accurate mass, 1I and 2I data.

531



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

532



Tables and Figures

533

534 535 536

Figure 1. Oven temperature program settings for the construction of isovolatility curves

537

(using a stepwise isothermal T program, solid line, for alkanes) and for GC×GC separation of

538

saffron (dashed line).


Page 21 of 26


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Page 20

539

540 541

Figure 2. 2D contour plots of saffron sample analysed by GC×GC–TOFMS with modulator

542

period of (A): 6 s and (B): 18 s. Display I: Corresponding total 1D chromatogram for data

543

projected onto the 1D axis. Display II: Corresponding total 2D chromatogram for data

544

projected into the 2D axis. Display III inset: Example of a single modulation taken at 21.2

545

min.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60



546 547 548

Figure 3. (A): 2D contour plot obtained with multiple injections of n-alkanes (C8-C22, C24)

549

in hexane analysed by GC×GC−TOFMS and (B): Two-dimensional retention map

550

(isovolatility curves) for the alkanes generated from three multiple injection experiments with

551

different stepwise isothermal T programs, an example of which is given in Figure 1 (solid

552

line).

553


Page 23 of 26


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Page 22

554 555 556

Figure 4. Flow chart showing the process of compound confirmation in GC×GC−TOFMS

557

involving the progressive application of total matches and retention index filters to refine the

558

data with an example that initially proposed 6 compounds that gave MS match factors ≥ 750,

559

then application of 1I and 2I to progressively reduce the number of possible compounds that

560

match retention indices within I ± 20, for identification of a peak at 1tR = 21.27 min and 2tR =

561

2.53 s.

562



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

563 564 565

566



Table 1. Comparison of 2I values for some compounds obtained in this study (Cal. 2I), and literature values (Literature I). Correlation between calculated and literature values gives an R2 of 0.9997. Literature Literature I Name Cal. 2I Errora I Reference C22b 2197 2200 -3 -c C21 2100 2100 0 C20 1996 2000 -4 C19 1904 1900 4 C18 1799 1800 -1 C17 1702 1700 2 C16 1602 1600 2 C15 1502 1500 2 C14 1404 1400 4 C13 1302 1300 2 C12 1203 1200 3 C11 1100 1100 0 C10 997 1000 -3 C9 899 900 -1 C8 801 800 1 31 2-Ethylhexanoic acid 1097 1123 -26 32 Phenol, 2,6-dimethyl1132 1130 2 33 Benzenamine, 2,3-dimethyl1202 1202 0 34 Dodecanoic acid, methyl ester 1527 1527 0 35 Undecanoic acid, methyl ester 1433 1427 6 d Cyclohexanamine, N-cyclohexyl1448 NA NA 34 Decanoic acid, methyl ester 1329 1328 1 36 1-Octanol 1081 1084 -3 37 Nonanal 1115 1108 7 a 2 Error = Calculated I - Literature I.

567

b

the number of carbon atoms Cn in the respective alkane.

568

c

the I values of alkanes are defined as n x 100, as a reference value.

569

d

the value cannot be calculated due to lack of a literature I value.

570


Page 25 of 26

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Analytical Chemistry

Jiang et al.


Page 24

571

Table 2. Tentatively identified compounds in the saffron sample analysed by GC×GC–TOFMS based on MS library, accurate mass, 1I and 2I

572

data calculated in this study (Cal. 1I and Cal. 2I). No. a

peak tR (min)b

5 7 11 12 13 15 18 22 25 29 31 32 38 42 45 48 51 54 55 59

12.462 14.062 15.156 15.266 15.369 15.564 15.866 16.159 16.365 17.258 17.470 17.671 18.262 18.869 19.465 20.161 20.364 21.168 21.272 23.356

62

24.495

63

24.680

C8H10 C7H14O C6H10O C9H12 C9H14O C8H16O C9H12 C 8 H8 C9H12 C6H10O C10H14 C10H14 C8H14O C10H14 C9H10 C7H10N2 C9H14O C10H14 C11H16 C 7 H6 O

Relative Conc (%) 0.01 0.13

Two-Dimensional Retention Indices Improve ... - ACS Publications

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